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Product
PMF, RICE, April Dunford positioning.
6B. PRODUCT
Authoritative Resources:
| Resource | Why It Matters |
|---|---|
| Lenny's Newsletter | 1.2M+ subscribers. Product management, growth, prioritization, career |
| First Round Review: Product | "Paths to PMF" series — real startup journeys (Applied Intuition $15B, Gamma, Guideline) |
| April Dunford: Obviously Awesome | The gold standard for product positioning (10-step methodology) |
| Marty Cagan: INSPIRED | Product team model — empowered teams, outcome vs output |
| Teresa Torres: Continuous Discovery Habits | Opportunity Solution Trees for structured discovery |
Core Frameworks:
- Product-Market Fit (PMF) — First Round's "Paths to PMF": find wedge → iterate on feedback → triple down on what works. No single formula, but pattern: solve an urgent problem for a narrow audience.
- Positioning (April Dunford) — 10 steps: competitive alternatives → unique attributes → value → target customer → market category → positioning statement. "If you can't position it, you can't sell it."
- RICE Scoring (Reach × Impact × Confidence / Effort) — prioritization at product/feature level
- Opportunity Solution Trees — Map desired outcomes → opportunities → solutions. Avoid build traps.
- Jobs to Be Done (JTBD) — Customers "hire" products for jobs. Drives strategy, not features.
- Shape Up — 6-week cycles, shaped vs unshaped work, appetite over estimates
How AI Changes Product:
- AI-native PMF: Gamma found PMF after pivoting to AI-native product (First Round case study). AI-first startups don't "add AI" — they rebuild from scratch around AI.
- AI user research synthesis: 10,000 support tickets → themes → opportunities in minutes
- AI spec generation: PM describes the problem; AI drafts user stories, acceptance criteria, edge cases
- AI prototyping: PMs wireframe, mock, and generate working front-end — the PM expands into rapid prototyping
- Role shift: from "feature delivery" → "outcome ownership." AI handles execution; PM focuses on strategy, psychology, business outcomes.
Product & Monetization Operating Rules
- Wedge first: validate one narrow, painful job and a reachable buyer before expanding into a platform or suite.
- Shared core, modular surface: when multiple products share tenancy, identity, billing, data, or workflow primitives, build those once and expose modules behind clear boundaries.
- Value-aligned pricing: keep entry pricing predictable, then align expansion to measurable usage or value. Cap or explain overage so customers can forecast.
- Paid discovery beats speculative breadth: a customer-funded implementation is strategically useful only when the contract protects reusable platform IP, isolates customer data/configuration, and creates a path to recurring support or resale.
- Impact still needs a payer: a real social problem is not automatically a viable business. Define the beneficiary, user, economic buyer, distribution path, and sustainable funding model separately.
- Price on countable activity: prefer transactions, invoices, payments collected, API calls, credits, SKUs, or completed workflow actions over unverifiable profit or revenue shares.
- Variable pricing is a trust system: show usage before payment, provide a grace buffer, cap or explain overage, and make the maximum plausible bill legible.
- Productize consulting before forcing SaaS: paid setup → repeatable workflow templates → managed service → multi-client platform → SaaS control plane. Productize only workflows that repeat across customers and retain.
- The moat is workflow depth and distribution: customer trust, local integrations, operating data, repeatable templates, and embedded workflows matter more than a specific agent runtime or model brand.
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